Awesome

MALMEN: MAssive Language Model Editing Network

This is the official repo of our ICLR'24 paper Massive Editing for Large Language Models via Meta Learning. You can email chenmien.tan@ed.ac.uk for any issue.

Setup

You can create a virtual environment and install the dependencies via Anaconda.

$ conda create -n malmen
$ conda activate malmen
(malmen)$ pip install -r requirements.txt

The datasets for all experiments presented in the manuscript are available at this Google Drive link. You need to specify the paths to the json files in config.data.train_path and config.data.valid_path. You should also specify an empty folder in config.editor.cache_dir to store cache files generated during running the code.

Running

You can set all hyper-parameters via modifying the yaml files in the folder config. You should run the code by executing the main.py file. You can also specify the hyper-parameters on the command line.

(malmen)$ python main.py  \
    data=zsre  \
    model=gpt-j  \
    editor=malmen

Acknowledgement

We thank the implementation of MEND and MEMIT, which inspires some code in this repo.

Citation

@inproceedings{tan23malmen,
    title={Massive Editing for Large Language Models via Meta Learning},
    author={Chenmien Tan and Ge Zhang and Jie Fu},
    booktitle={International Conference on Learning Representations},
    year={2024},
    url={https://openreview.net/pdf?id=L6L1CJQ2PE}
}